def regions(self):
""" regions created for the top proposals"""
region_fn = os.path.join(self.ds.path, 'cpmc', 'MySegmentsMat', self.name, 'top_regions.mat')
if os.path.exists(region_fn):
regions = ml.loadmat(region_fn)['top_regions']
else:
proposals = self.top_masks
regions = reg.produce_regions(proposals)
ml.savemat(region_fn, {'top_regions':regions})
logging.debug("Storing regions in %s" % region_fn)
if not np.any(np.isnan(regions)):
logging.debug("All pixels are covered in one region")
return regions
def regions(self):
""" regions created for the top proposals"""
region_fn = os.path.join(self.ds.path, "cpmc", "MySegmentsMat", self.name, "top_regions.mat")
if os.path.exists(region_fn):
regions = ml.loadmat(region_fn)["top_regions"]
else:
proposals = self.top_masks
regions = reg.produce_regions(proposals)
ml.savemat(region_fn, {"top_regions": regions})
logging.debug("Storing regions in %s" % region_fn)
if not np.any(np.isnan(regions)):
logging.debug("All pixels are covered in one region")
return regions
num = 12
for i in range(num):
ax = prepare_jpg_plot()
mask = masks[:, :, i]
mask[mask > 0] = 6
util.visual.show_image_mask(img, mask, ax, alpha=0.9)
fn = 'segment_{:0=2d}.jpg'.format(i + 1)
util.visual.add_inner_title(ax,
"Score: {:.4}".format(scores[i]),
3,
size={
"size": 45,
"color": "w"
})
save_plot(fn, path)
regs = regions.produce_regions(masks[:, :, :num])
ax = prepare_jpg_plot()
ax.imshow(regs,
cmap=mpl.colors.ListedColormap(np.random.rand(256, 3)),
interpolation="nearest")
save_plot("regions.png", path)
ax = prepare_jpg_plot()
reg = img.regions
ax.imshow(reg,
cmap=mpl.colors.ListedColormap(np.random.rand(256, 3)),
interpolation='nearest')
ax.set_axis_off()
save_plot("regions_all.png", path)
ax = prepare_jpg_plot()
n = "2007_005331"
img = ds.voc2010_trainval[ds.voc2010_trainval.names.index(n)]
masks = img.top_masks
scores = img.get_top_scores()
num = 12
for i in range(num):
ax = prepare_jpg_plot()
mask = masks[:,:,i]
mask[mask > 0] = 6
util.visual.show_image_mask(img, mask, ax, alpha=0.9)
fn = 'segment_{:0=2d}.jpg'.format(i+1)
util.visual.add_inner_title(ax, "Score: {:.4}".format(scores[i]), 3, size={"size":45, "color":"w"})
save_plot(fn, path)
regs = regions.produce_regions(masks[:,:,:num])
ax = prepare_jpg_plot()
ax.imshow(regs,cmap=mpl.colors.ListedColormap ( np.random.rand ( 256,3)), interpolation="nearest")
save_plot("regions.png", path)
ax = prepare_jpg_plot()
reg = img.regions
ax.imshow(reg,cmap=mpl.colors.ListedColormap ( np.random.rand ( 256,3)) ,interpolation='nearest')
ax.set_axis_off()
save_plot("regions_all.png", path)
ax = prepare_jpg_plot()
util.visual.show_annotated_image(img, ax, show_bg=True, alpha=1.)
save_plot("gt.jpg", path)
ax = prepare_jpg_plot()